相关实验视频

对XGBoost和混合CnnSVM的超参数优化,用于使用修改后的哈里斯·霍克斯算法进行网络威胁检测

Haitham Elwahsh1,2, Ali Bakhiet3, Tarek Khalifa4

  • 1Faculty of Information Technology, Applied Science University, Amman, Jordan.

PeerJ. Computer science
|September 24, 2025
PubMed
概括

这项研究介绍了一种新的智能微电网网络威胁检测框架,使用哈里斯·霍克斯优化 (HHO) 来增强机器学习模型. 优化的模型在检测复杂的网络攻击方面实现了超过99.97%的准确性.

关键词:
在CnnSVM中使用.网络攻击 网络攻击哈里斯·霍克斯优化 (HHO) 的优化优化机器学习的优化在XGBoost上使用.

相关概念视频

Survival Tree01:19

Survival Tree

Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
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